Enzyminator 3000


Overview

All proccesses in cells rely on chemical reactions, which can require lots of energy. The Second Law of Thermodynamics suggests that entropy, or disorder, naturally tends to increase, but life itself seems to contradict that, with it definiteionallyy being the organization of matter in a self-sustaining system.

Here's where enzymes come it. Enzymes are vital catalysts in these cells to lower the activation energy needed for biological processes. As such, when producing a large quantity of a product or needing to produce a response quickly, enzymes are almost always used to . The program modularly mimics the chaotic "random" collision in a cell to model how long it takes for a substrate to reach an enzyme.


The Program

The following properties will be variable:

In the first mode, these particles will be added in a random configuration of positions and velocity directions, with an animation plyaing out until an enzyme and substrate collide and a reaction occurs. The number of steps will then be displayed.

In the second mode, the program goes through multiple trials with varying numbers of substrate particles. The program averages these out and plots the number of substrate particles against the reaction time in a bar graph with error bars. It should theoretically show an inverse relationship as the reaction time decreases as substrate particles increase.


Conclusion

Here is a demonstration of the Brownian motion in a cell:

Fast

With all the water molecules in the way, it is very inefficient, taking lots of time to react. If we increase the temperature by 4 times (effectively doubling the initial velocity), the reaction rate does increase.

Fast

However, increasing temperature is not a good idea in cells because these enzymes only work in a narrow range of temperatures and will denature otherwise. Instead, cells just produce many redundant copies of substrates or enzymes to increase the reaction rate. Here, we've added 2 more substrates.

More Substrates

To investigate the effect of the number of substrates of reaction rate, we varied the number of substrate particles while keeping all else constant and measured the average number of steps for one of them to meet an enzyme. Here is the data collected:

Substrate v. Reaction Time Graph

The graph shows a clear inversely trend. As the number of substrate particles increases demonstrates an increase in reaction rate, the average reaction time decreases. The time decreases rapidly at first but eventually tapers off, as demonstrated by the 95% error bars, which are distinct between trials at lower numbers but overlap at higher levels. This makes sense as an increase from 1 to 2 is a much larger relative change when compared to 13 to 14. In addition, adding more and more substrates leads to diminishing returns as the reaction rate's limiting factor becomes the number of available enzymes instead of substrates.

To conclude, the model shows that as the number of substrates increases, so does the reaction rate of enzymes.